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  • Hydrology and Earth System Sciences (HESS)

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  • Open Access English
    Authors: 
    J. Janapati; B. K. Seela; P.-L. Lin; P.-L. Lin; P.-L. Lin; M.-T. Lee; E. Joseph; E. Joseph;
    Publisher: Copernicus Publications

    Information about the raindrop size distribution (RSD) is vital for comprehending the precipitation microphysics, improving the rainfall estimation algorithms, and appraising the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which leads to the assessment of the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in northern Taiwan, this study attempts to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of large-sized drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (Dm) and lower normalized intercept parameter (Nw) values in NTY than TY rainfall. Moreover, sorting these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes revealed a larger Dm in NTY than in TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z–R, Dm–R, and Nw–R) and rainfall kinetic energy (KE–R and KE–Dm) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermodynamical and microphysical processes are elucidated with the aid of reanalysis, remote sensing, and ground-based data sets.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Shawn J. Marshall;
    Publisher: Copernicus Publications
    Project: NSERC

    Abstract. Observations of high-elevation meteorological conditions, glacier mass balance, and glacier run-off are sparse in western Canada and the Canadian Rocky Mountains, leading to uncertainty about the importance of glaciers to regional water resources. This needs to be quantified so that the impacts of ongoing glacier recession can be evaluated with respect to alpine ecology, hydroelectric operations, and water resource management. In this manuscript the seasonal evolution of glacier run-off is assessed for an alpine watershed on the continental divide in the Canadian Rocky Mountains. The study area is a headwaters catchment of the Bow River, which flows eastward to provide an important supply of water to the Canadian prairies. Meteorological, snowpack, and surface energy balance data collected at Haig Glacier from 2002 to 2013 were analysed to evaluate glacier mass balance and run-off. Annual specific discharge from snow- and ice-melt on Haig Glacier averaged 2350 mm water equivalent from 2002 to 2013, with 42% of the run-off derived from melting of glacier ice and firn, i.e. water stored in the glacier reservoir. This is an order of magnitude greater than the annual specific discharge from non-glacierized parts of the Bow River basin. From 2002 to 2013, meltwater derived from the glacier storage was equivalent to 5–6% of the flow of the Bow River in Calgary in late summer and 2–3% of annual discharge. The basin is typical of most glacier-fed mountain rivers, where the modest and declining extent of glacierized area in the catchment limits the glacier contribution to annual run-off.

  • Open Access English
    Authors: 
    Hartmut Holländer; Helge Bormann; Theresa Blume; Wouter Buytaert; Giovanni Battista Chirico; Jean-François Exbrayat; David Gustafsson; H. Hölzel; T. Krauße; Philipp Kraft; +3 more
    Publisher: Copernicus Publications
    Countries: Switzerland, Germany

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers – using the model of their choice – for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements. Hydrology and Earth System Sciences, 18 (6) ISSN:1027-5606 ISSN:1607-7938

  • Open Access English
    Authors: 
    H. Cai; H. Cai; P. Zhang; P. Zhang; E. Garel; P. Matte; S. Hu; S. Hu; F. Liu; F. Liu; +2 more
    Country: Portugal

    Assessing the impacts of both natural (e.g., tidal forcing from the ocean) and human-induced changes (e.g., dredging for navigation, land reclamation) on estuarine morphology is particularly important for the protection and management of the estuarine environment. In this study, a novel analytical approach is proposed for the assessment of estuarine morphological evolution in terms of tidally averaged depth on the basis of the observed water levels along the estuary. The key lies in deriving a relationship between wave celerity and tidal damping or amplification. For given observed water levels at two gauging stations, it is possible to have a first estimation of both wave celerity (distance divided by tidal travelling time) and tidal damping or amplification rate (tidal range difference divided by distance), which can then be used to predict the morphological changes via an inverse analytical model for tidal hydrodynamics. The proposed method is applied to the Lingdingyang Bay of the Pearl River Estuary, located on the southern coast of China, to analyse the historical development of the tidal hydrodynamics and morphological evolution. The analytical results show surprisingly good correspondence with observed water depth and volume in this system. The merit of the proposed method is that it provides a simple approach for understanding the decadal evolution of the estuarine morphology through the use of observed water levels, which are usually available and can be easily measured. National Key R&D of China (Grant No. 2016YFC0402601), National Natural Science Foundation of China (Grant No. 51979296, 51709287, 41706088, 41476073), Fundamental Research Funds for the Central Universities (No.18lgpy29) and from the Water Resource Science and Technology Innovation Program of Guangdong Province (Grant No. 2016-20, 2016-21). The work of the second author was supported by FCT research contracts IF/00661/2014/CP1234. info:eu-repo/semantics/submittedVersion

  • Open Access English
    Authors: 
    C. Scudeler; C. Scudeler; L. Pangle; D. Pasetto; G.-Y. Niu; G.-Y. Niu; T. Volkmann; C. Paniconi; M. Putti; P. Troch; +1 more
    Publisher: Copernicus Publications
    Countries: Italy, Switzerland
    Project: NSF | COLLABORATIVE RESEARCH: C... (1417097), NSF | Collaborative Research: H... (1344552)

    Abstract. This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection–dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.

  • Open Access English
    Authors: 
    A. Maclean; Bryan A. Tolson; Frank Seglenieks; Eric D. Soulis;

    Abstract. The spatially distributed MESH hydrologic model (Pietroniro et al., 2007) was successfully calibrated and then validated for the prediction of snow water equivalent (SWE) and streamflow in the Reynolds Creek Experimental Watershed in Idaho, USA. The tradeoff between fitting to SWE versus streamflow data was assessed and showed that both could be simultaneously predicted with good quality by the MESH model. Not surprisingly, calibrating to only one objective (e.g. SWE) yielded poor simulation results for the other objective (e.g. streamflow). The multiobjective calibration problem in this study was efficiently solved via a simple weighted objective function approach and analyses showed that the approach yielded a balanced solution between the objectives. Our approach therefore eliminated the need to rely on a potentially more computationally intensive evolutionary multiobjective algorithm to approximate the entire tradeoff surface between objectives. Additional calibration experiments showed that for our calibration computational budget (2000 model evaluations), the autocalibration procedure would fail without being initialized to a model parameter set carefully determined for this specific case study. This study serves as a benchmark for MESH model simulation accuracy which can be compared with future versions of MESH.

  • Open Access English
    Authors: 
    Anaïs Barella-Ortiz; Jan Polcher; Patricia de Rosnay; Maria Piles; Emiliano Gelati;
    Publisher: Copernicus Publications
    Countries: Spain, France, Spain
    Project: EC | EARTH2OBSERVE (603608)

    L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies This work contributes to the FP7 Earth2Observe project under grant agreement no. 603608 19 pges, 10 figures, 6 tables Peer Reviewed

  • Publication . Article . Preprint . Other literature type . 2015
    Open Access English
    Authors: 
    Justin F. Costelloe; Tim J. Peterson; K. Halbert; Andrew W. Western; Jeffrey J. McDonnell;
    Project: ARC | A new method for identify... (DP120100253)

    Abstract. Groundwater discharge is a major contributor to stream baseflow. Quantifying this flux is difficult, despite its considerable importance to water resource management and evaluation of the effects of groundwater extraction on streamflow. It is important to be able to differentiate between contributions to streamflow from regional groundwater discharge (more susceptible to groundwater extraction) compared to interflow processes (arguably less susceptible to groundwater extraction). Here we explore the use of unconfined groundwater surface mapping as an independent dataset to constrain estimates of groundwater discharge to streamflow using traditional digital filter and tracer techniques. We developed groundwater surfaces from 98 monitoring bores using Kriging with external drift. Baseflow estimates at the catchment outlet were made using the Eckhardt digital filter approach and tracer data mixing analysis using major ion and stable isotope signatures. Our groundwater mapping approach yielded two measures (percentage area intersecting the land surface and monthly change in saturated volume) that indicated that digital filter-derived baseflow significantly exceeded probable groundwater discharge during the high flow period of spring to early summer. Tracer analysis was not able to resolve contributions from ungauged tributary flows (sourced from either shallow flow paths, i.e. interflow and perched aquifer discharge, or regional groundwater discharge) and regional groundwater. Groundwater mapping was able to identify ungauged sub-catchments where regional groundwater discharge was too deep to contribute to tributary flow and thus where shallow flow paths dominated the tributary flow. Our results suggest that kriged unconfined groundwater surfaces provide a useful, empirical and independent dataset for investigating sources of fluxes contributing to baseflow and identifying periods where baseflow analysis may overestimate groundwater discharge to streamflow.

  • Open Access English
    Authors: 
    Émilie Poirier; Julie M. Thériault; Maud Leriche;
    Publisher: HAL CCSD
    Country: France
    Project: NSERC

    The phase of precipitation and its distribution at the surface can affect water resources and the regional water cycle of a region. A field project was held in March–April 2015 on the eastern slope of the Canadian Rockies to document precipitation characteristics and associated atmospheric conditions. During the project, 60 % of the particles documented were rimed in relatively warm and dry conditions. Rain–snow transitions also occurred aloft and at the surface in sub-saturated conditions. Ice-phase precipitation falling through a saturated atmospheric layer with temperatures > 0 ∘C will start melting. In contrast, if the melting layer is sub-saturated, the ice-phase precipitation undergoes sublimation, which increases the depth of the rain–snow transition. In this context, this study investigates the role of sublimation and riming in precipitation intensity and type reaching the surface in the Kananaskis Valley, Alberta, during March–April 2015. To address this, a set of numerical simulations of an event of mixed precipitation observed at the surface was conducted. This event on 31 March 2015 was documented with a set of devices at the main observation site (Kananaskis Emergency Services, KES), including a precipitation gauge, disdrometer, and micro rain radar. Sensitivity experiments were performed to assess the impacts of temperature changes from sublimation and the role of the production of graupel (riming) aloft in the surface precipitation evolution. A warmer environment associated with no temperature changes from sublimation leads to a peak in the intensity of graupel at the surface. When the formation of graupel is not considered, the maximum snowfall rate occurred at later times. Results suggest that unrimed snow reaching the surface is formed on the western flank and is advected eastward. In contrast, graupel would form aloft in the Kananaskis Valley. The cooling from sublimation and melting by rimed particles increases the vertical shear near KES. Overall, this study illustrated that the presence of graupel influenced the surface evolution of precipitation type in the valley due to the horizontal transport of precipitation particles.

  • Open Access English
    Authors: 
    Abdalla Osman; Mohammed Falah Allawi; Haitham Abdulmohsin Afan; Aboelmagd Noureldin; Ahmed El-Shafie;

    Abstract. River stream-flow is well-thought-out as an essential element in the hydrology studies, especially for reservoir management. Forecasting river stream-flow is the key for the hydrologists in proposing certain short or long-term planning and management for water resources system. In fact, developing stream-flow forecasting models are generally categorized into two main classes; process and data-driven model. Different model techniques based on empirical methods, such as stochastic model or regression model, more recently, Artificial Intelligent (AI) models have been examined and could provide accurate stream-flow forecasting. However, AI models experienced crucial difficulty is the necessity to utilize appropriate pre-processing methods for the raw data. In addition, the AI model should be augmented with proper optimization model to adjust the model parameters to achieve the optimal accuracy. In this paper, a novel model namely; Fast Orthogonal Search (FOS) model is proposed to develop river stream-flow forecasting. FOS is basically structured for recognizing the difference equation and its functional expression model for the mapping between the model input and output. The major advantage of using FOS is the waiver of the requirement of data pre-processing and optimization model for model parameters adjustment as these procedures are performed implicitly inside FOS. In addition, pole-zero cancellation procedure within FOS process can detect the over-fitted models and avoid them. The proposed FOS method was adopted in this research to perform stream-flow forecasting model at Aswan High Dam using monthly basis for130 years. Results showed outstanding performance for stream-flow forecasting accuracy compared to other AI models developed during the last 10 years.

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Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
250 Research products, page 1 of 25
  • Open Access English
    Authors: 
    J. Janapati; B. K. Seela; P.-L. Lin; P.-L. Lin; P.-L. Lin; M.-T. Lee; E. Joseph; E. Joseph;
    Publisher: Copernicus Publications

    Information about the raindrop size distribution (RSD) is vital for comprehending the precipitation microphysics, improving the rainfall estimation algorithms, and appraising the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which leads to the assessment of the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in northern Taiwan, this study attempts to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of large-sized drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (Dm) and lower normalized intercept parameter (Nw) values in NTY than TY rainfall. Moreover, sorting these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes revealed a larger Dm in NTY than in TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z–R, Dm–R, and Nw–R) and rainfall kinetic energy (KE–R and KE–Dm) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermodynamical and microphysical processes are elucidated with the aid of reanalysis, remote sensing, and ground-based data sets.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Shawn J. Marshall;
    Publisher: Copernicus Publications
    Project: NSERC

    Abstract. Observations of high-elevation meteorological conditions, glacier mass balance, and glacier run-off are sparse in western Canada and the Canadian Rocky Mountains, leading to uncertainty about the importance of glaciers to regional water resources. This needs to be quantified so that the impacts of ongoing glacier recession can be evaluated with respect to alpine ecology, hydroelectric operations, and water resource management. In this manuscript the seasonal evolution of glacier run-off is assessed for an alpine watershed on the continental divide in the Canadian Rocky Mountains. The study area is a headwaters catchment of the Bow River, which flows eastward to provide an important supply of water to the Canadian prairies. Meteorological, snowpack, and surface energy balance data collected at Haig Glacier from 2002 to 2013 were analysed to evaluate glacier mass balance and run-off. Annual specific discharge from snow- and ice-melt on Haig Glacier averaged 2350 mm water equivalent from 2002 to 2013, with 42% of the run-off derived from melting of glacier ice and firn, i.e. water stored in the glacier reservoir. This is an order of magnitude greater than the annual specific discharge from non-glacierized parts of the Bow River basin. From 2002 to 2013, meltwater derived from the glacier storage was equivalent to 5–6% of the flow of the Bow River in Calgary in late summer and 2–3% of annual discharge. The basin is typical of most glacier-fed mountain rivers, where the modest and declining extent of glacierized area in the catchment limits the glacier contribution to annual run-off.

  • Open Access English
    Authors: 
    Hartmut Holländer; Helge Bormann; Theresa Blume; Wouter Buytaert; Giovanni Battista Chirico; Jean-François Exbrayat; David Gustafsson; H. Hölzel; T. Krauße; Philipp Kraft; +3 more
    Publisher: Copernicus Publications
    Countries: Switzerland, Germany

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers – using the model of their choice – for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements. Hydrology and Earth System Sciences, 18 (6) ISSN:1027-5606 ISSN:1607-7938

  • Open Access English
    Authors: 
    H. Cai; H. Cai; P. Zhang; P. Zhang; E. Garel; P. Matte; S. Hu; S. Hu; F. Liu; F. Liu; +2 more
    Country: Portugal

    Assessing the impacts of both natural (e.g., tidal forcing from the ocean) and human-induced changes (e.g., dredging for navigation, land reclamation) on estuarine morphology is particularly important for the protection and management of the estuarine environment. In this study, a novel analytical approach is proposed for the assessment of estuarine morphological evolution in terms of tidally averaged depth on the basis of the observed water levels along the estuary. The key lies in deriving a relationship between wave celerity and tidal damping or amplification. For given observed water levels at two gauging stations, it is possible to have a first estimation of both wave celerity (distance divided by tidal travelling time) and tidal damping or amplification rate (tidal range difference divided by distance), which can then be used to predict the morphological changes via an inverse analytical model for tidal hydrodynamics. The proposed method is applied to the Lingdingyang Bay of the Pearl River Estuary, located on the southern coast of China, to analyse the historical development of the tidal hydrodynamics and morphological evolution. The analytical results show surprisingly good correspondence with observed water depth and volume in this system. The merit of the proposed method is that it provides a simple approach for understanding the decadal evolution of the estuarine morphology through the use of observed water levels, which are usually available and can be easily measured. National Key R&D of China (Grant No. 2016YFC0402601), National Natural Science Foundation of China (Grant No. 51979296, 51709287, 41706088, 41476073), Fundamental Research Funds for the Central Universities (No.18lgpy29) and from the Water Resource Science and Technology Innovation Program of Guangdong Province (Grant No. 2016-20, 2016-21). The work of the second author was supported by FCT research contracts IF/00661/2014/CP1234. info:eu-repo/semantics/submittedVersion

  • Open Access English
    Authors: 
    C. Scudeler; C. Scudeler; L. Pangle; D. Pasetto; G.-Y. Niu; G.-Y. Niu; T. Volkmann; C. Paniconi; M. Putti; P. Troch; +1 more
    Publisher: Copernicus Publications
    Countries: Italy, Switzerland
    Project: NSF | COLLABORATIVE RESEARCH: C... (1417097), NSF | Collaborative Research: H... (1344552)

    Abstract. This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection–dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.

  • Open Access English
    Authors: 
    A. Maclean; Bryan A. Tolson; Frank Seglenieks; Eric D. Soulis;

    Abstract. The spatially distributed MESH hydrologic model (Pietroniro et al., 2007) was successfully calibrated and then validated for the prediction of snow water equivalent (SWE) and streamflow in the Reynolds Creek Experimental Watershed in Idaho, USA. The tradeoff between fitting to SWE versus streamflow data was assessed and showed that both could be simultaneously predicted with good quality by the MESH model. Not surprisingly, calibrating to only one objective (e.g. SWE) yielded poor simulation results for the other objective (e.g. streamflow). The multiobjective calibration problem in this study was efficiently solved via a simple weighted objective function approach and analyses showed that the approach yielded a balanced solution between the objectives. Our approach therefore eliminated the need to rely on a potentially more computationally intensive evolutionary multiobjective algorithm to approximate the entire tradeoff surface between objectives. Additional calibration experiments showed that for our calibration computational budget (2000 model evaluations), the autocalibration procedure would fail without being initialized to a model parameter set carefully determined for this specific case study. This study serves as a benchmark for MESH model simulation accuracy which can be compared with future versions of MESH.

  • Open Access English
    Authors: 
    Anaïs Barella-Ortiz; Jan Polcher; Patricia de Rosnay; Maria Piles; Emiliano Gelati;
    Publisher: Copernicus Publications
    Countries: Spain, France, Spain
    Project: EC | EARTH2OBSERVE (603608)

    L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies This work contributes to the FP7 Earth2Observe project under grant agreement no. 603608 19 pges, 10 figures, 6 tables Peer Reviewed

  • Publication . Article . Preprint . Other literature type . 2015
    Open Access English
    Authors: 
    Justin F. Costelloe; Tim J. Peterson; K. Halbert; Andrew W. Western; Jeffrey J. McDonnell;
    Project: ARC | A new method for identify... (DP120100253)

    Abstract. Groundwater discharge is a major contributor to stream baseflow. Quantifying this flux is difficult, despite its considerable importance to water resource management and evaluation of the effects of groundwater extraction on streamflow. It is important to be able to differentiate between contributions to streamflow from regional groundwater discharge (more susceptible to groundwater extraction) compared to interflow processes (arguably less susceptible to groundwater extraction). Here we explore the use of unconfined groundwater surface mapping as an independent dataset to constrain estimates of groundwater discharge to streamflow using traditional digital filter and tracer techniques. We developed groundwater surfaces from 98 monitoring bores using Kriging with external drift. Baseflow estimates at the catchment outlet were made using the Eckhardt digital filter approach and tracer data mixing analysis using major ion and stable isotope signatures. Our groundwater mapping approach yielded two measures (percentage area intersecting the land surface and monthly change in saturated volume) that indicated that digital filter-derived baseflow significantly exceeded probable groundwater discharge during the high flow period of spring to early summer. Tracer analysis was not able to resolve contributions from ungauged tributary flows (sourced from either shallow flow paths, i.e. interflow and perched aquifer discharge, or regional groundwater discharge) and regional groundwater. Groundwater mapping was able to identify ungauged sub-catchments where regional groundwater discharge was too deep to contribute to tributary flow and thus where shallow flow paths dominated the tributary flow. Our results suggest that kriged unconfined groundwater surfaces provide a useful, empirical and independent dataset for investigating sources of fluxes contributing to baseflow and identifying periods where baseflow analysis may overestimate groundwater discharge to streamflow.

  • Open Access English
    Authors: 
    Émilie Poirier; Julie M. Thériault; Maud Leriche;
    Publisher: HAL CCSD
    Country: France
    Project: NSERC

    The phase of precipitation and its distribution at the surface can affect water resources and the regional water cycle of a region. A field project was held in March–April 2015 on the eastern slope of the Canadian Rockies to document precipitation characteristics and associated atmospheric conditions. During the project, 60 % of the particles documented were rimed in relatively warm and dry conditions. Rain–snow transitions also occurred aloft and at the surface in sub-saturated conditions. Ice-phase precipitation falling through a saturated atmospheric layer with temperatures > 0 ∘C will start melting. In contrast, if the melting layer is sub-saturated, the ice-phase precipitation undergoes sublimation, which increases the depth of the rain–snow transition. In this context, this study investigates the role of sublimation and riming in precipitation intensity and type reaching the surface in the Kananaskis Valley, Alberta, during March–April 2015. To address this, a set of numerical simulations of an event of mixed precipitation observed at the surface was conducted. This event on 31 March 2015 was documented with a set of devices at the main observation site (Kananaskis Emergency Services, KES), including a precipitation gauge, disdrometer, and micro rain radar. Sensitivity experiments were performed to assess the impacts of temperature changes from sublimation and the role of the production of graupel (riming) aloft in the surface precipitation evolution. A warmer environment associated with no temperature changes from sublimation leads to a peak in the intensity of graupel at the surface. When the formation of graupel is not considered, the maximum snowfall rate occurred at later times. Results suggest that unrimed snow reaching the surface is formed on the western flank and is advected eastward. In contrast, graupel would form aloft in the Kananaskis Valley. The cooling from sublimation and melting by rimed particles increases the vertical shear near KES. Overall, this study illustrated that the presence of graupel influenced the surface evolution of precipitation type in the valley due to the horizontal transport of precipitation particles.

  • Open Access English
    Authors: 
    Abdalla Osman; Mohammed Falah Allawi; Haitham Abdulmohsin Afan; Aboelmagd Noureldin; Ahmed El-Shafie;

    Abstract. River stream-flow is well-thought-out as an essential element in the hydrology studies, especially for reservoir management. Forecasting river stream-flow is the key for the hydrologists in proposing certain short or long-term planning and management for water resources system. In fact, developing stream-flow forecasting models are generally categorized into two main classes; process and data-driven model. Different model techniques based on empirical methods, such as stochastic model or regression model, more recently, Artificial Intelligent (AI) models have been examined and could provide accurate stream-flow forecasting. However, AI models experienced crucial difficulty is the necessity to utilize appropriate pre-processing methods for the raw data. In addition, the AI model should be augmented with proper optimization model to adjust the model parameters to achieve the optimal accuracy. In this paper, a novel model namely; Fast Orthogonal Search (FOS) model is proposed to develop river stream-flow forecasting. FOS is basically structured for recognizing the difference equation and its functional expression model for the mapping between the model input and output. The major advantage of using FOS is the waiver of the requirement of data pre-processing and optimization model for model parameters adjustment as these procedures are performed implicitly inside FOS. In addition, pole-zero cancellation procedure within FOS process can detect the over-fitted models and avoid them. The proposed FOS method was adopted in this research to perform stream-flow forecasting model at Aswan High Dam using monthly basis for130 years. Results showed outstanding performance for stream-flow forecasting accuracy compared to other AI models developed during the last 10 years.